The Effect of Wind Turbines on Property Values: A New Study in Massachusetts Provides Some Answers

A new study looked at how well wind turbines and homes fit together in Massachusetts, and found no evidence that wind turbines affect property values. That finding is consistent with other recent work from a range of states across the country. And it’s good news for everybody wanting to get wind turbines sited responsibly, in the Bay State and beyond.

Wind turbines in a denser state

For the new work, the researchers zeroed in on Massachusetts. The state is important in this case because it has very different circumstances, people-wise, from places the 2013 work studied. Specifically, it’s got a lot more people in a lot tighter spaces:

The average gross population density surrounding the Massachusetts turbines (approximately 416 persons per square mile…) far exceeds the national average of approximately 11 persons per square mile around turbines…

Given that difference, the study set out to explore whether home values are affected by wind turbines, or announced plans to build them, in Massachusetts.

To figure out the answer, the research took in more than 122,000 home sales from 1998 to 2012 in the state that were near existing or future “utility-scale” wind turbines. Most were single wind turbines; others were in groups of two, three, or, in one case, 10. The data included 7,188 sales that were within a mile of a turbine, including 1,503 after the relevant turbine was installed.

No measurable impact on property values

Gloucester’s majestic wind turbines were too new to be included in the study, but clearly relevant to the topic at hand. And awfully picturesque. (Source: J. Rogers)

The study’s conclusion was that, except maybe briefly after a given project had been announced and before it had been built, there was no measurable impact on property values. Fromthe report (emphasis added):

The results of this study do not support the claim that wind turbines affect nearby home prices. Although the study found the effects on home prices from a variety of negative features (such as electricity transmission lines, landfills, prisons and major roads) and positive features (such as open space and beaches) that accorded with previous studies, the study found no net effects due to the arrival of turbines in the sample’s communities. Weak evidence suggests that the announcement of the wind facilities had an adverse impact on home prices, but those effects were no longer apparent after turbine construction and eventual operation commenced. The analysis also showed no unique impact on the rate of home sales near wind turbines. These conclusions were the result a variety of model and sample specifications.

To put those home-price findings in perspective, the study also offered information on how turbines stack up against a range of “amenities” and “disamenities” in Massachusetts, according to the new research. The results, shown in the graphic below, suggest that landfills, transmission lines, and highways aren’t good for property values; beaches are; and wind turbines probably fall in between.

As with the previous LBNL study, this one doesn’t say that wind turbines are never an impact for anybody. Different people react differently to turbines, and some people clearly feel more passionate about them, pro or anti, than others. Here’s how this handy FAQ from the Massachusetts Clean Energy Center, which supported the research, puts it (emphasis added):

The findings of the study suggest that a house’s price should not be discounted because it is near a turbine. As with all characteristics of a particular property, a house’s proximity to a turbine may dissuade some buyers, but the fact that people do buy houses near turbines suggests that not all potential buyers share the same view about turbines.

It’s really handy, though, to have more and more data showing just how well wind turbines and homes fit together.

Wind energy is a key tool for our transition to a clean energy future, and understanding issues like effects on property values is a key part of making wind happen appropriately — from “the mountainous Berkshire East Ski Resort, [to] heavily urbanized Charlestown,… [to] picturesque Cape Cod” — and beyond.

Support from UCS members make work like this possible. Will you join us? Help UCS advance independent science for a healthy environment and a safer world.

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Bill Heller

Regarding industrial wind installations…and please be honest…would anyone reading this really consider investing their hard-earned dollars in a home 1,000 feet away from a 40-story noisy industrial machine with blades each at least the size of a cell tower? I doubt the majority of you really would. Yet, that’s what USC is demanding…that people be good green patriots and gladly accept this industrial intrusion. To believe that an invasion of industrial wind turbines into a previously quiet area with no tall structures would not hurt home values is deluded. Ben Hoen, the lead author, is the wind industry’s go-to-guy for studies like these. But in an interview, even he has stated that his studies are being taken out of context and that wind developers should offer a home-value guarantee, since they promote the notion the there is no impact:http://www.wind-watch.org/documents/ben-hoen-on-need-for-property-value-guarantee/
Here is a good article rebutting the Massachusetts study by a licensed appraiser with experience in properties abutting wind turbines:https://www.wind-watch.org/documents/regarding-ben-hoen-study-on-residential-property-values/
And a few other links regarding wind turbines & home values:
1) http://www.windturbinepropertyloss.org/
2) http://tinyurl.com/k5h4yoy (Mother Earth News, a big green publication, acknowledges turbines kill values)
3) http://tinyurl.com/khtfqn6 (A study from Clarkson University)
4) http://www.ens.dk/node/2021 (Denmark requires wind developers to compensate home owners – why would they do that if home values were not a serious issue?)
The UCS, like other pro-wind lobbying groups, is way too eager to back big industry over working class homeowners and threatened avian and bat populations.

Thanks, Bill. Apparently many people do consider investing their hard-earned dollars in homes near turbines; that’s what the data show. People — not everybody, and maybe not the majority — buy houses close to lots of “disamenities”, such as highways and landfills. The point of this study was to evaluate how the market had responded to wind turbines, and to use data, not stories, to assess that. And the answer is that it appears not to lump them in with disamenities or amenities; it’s neutral.

Good decision making depends on having access to good data well-analyzed and transparent processes, and basing more of our decisions on such options than on anecdotes, press releases, or Photoshopped vistas. That’s why studies like this one are so important.

Virginia Irvine

One would think that a prestigious organization like the Union of Concerned Scientists would not take a study at face value when it was funded by a quasi-public state agency which is not neutral on the issue of wind turbines.

The first thing one should look at is the methodology. The accepted appraisal methodology was not used in the study. It measures value impact on damages caused by a neighboring land use, through such methods as “paired sales” or “resale” analysis.

Instead, the hedonic method lends itself to a compounding effect of any errors in judgment, or even intentional over- or under-emphasis of values contributed by other variables. In fact, the U.S. Court of Appeals for the First Circuit expressed serious doubts about hedonic damages being a reliable measure of value. The court said the expert’s opinion was based on assumptions “that appear to controvert logic and good sense.”

Anyone really serious about finding the impact of wind turbines on property values should review Multiple Listing Service data, as well as expired and cancelled listing comparisons, for homes that no one will buy (because they are situated near turbines). In the entire study, not a single property sale is cited. Using standard data, independent appraisers have found that homes near wind turbines plummet in value from 15% to 40%.

The Hoen study included homes that were as far as five miles from the turbines. No one would expect those homes to lose value. The fact that the Hoen study uses 122,000 “sales” (although not a single property sale is identified) is also misleading. Only a miniscule number of those transactions are likely to have been affected by neighboring turbines, so the actual impacts get lost in the rounding of statistical analysis.

In order for comparisons to be valid from an appraisal perspective, the impacts of near vs. far data must be measured on a 1:1 basis. This is the paired sales methodology. Measuring on a 500:1 or 1,000:1 basis allows the research and conclusions to be manipulated, as any statistician would attest.

In addition to methodology, readers should question the study because it is funded by a quasi-public agency dedicated to siting wind turbines in Massachusetts.

Scientists would do well to look past the appearance of valid findings to consider the flaws and biases before accepting studies like this at face value.

Thank you for the compliment, Virginia. We work hard to put rigorous, independent science to work to address a whole range of issues — including unsustainability in the energy sector.

The methodology used for this study was certainly not something they pulled out of hat, and while you may not like its findings, you may need to find other strategies for pushing back on the results. The FAQ I pointed to is clear about the process:

“The study underwent a peer review process similar to what other studies undergo prior to publication in academic journals. During the peer review process, a team of independent experts from multiple universities and with diverse backgrounds reviewed all aspects of the report. In particular, they focused on the report’s methods, results and conclusions to determine that all statistical tests have been applied properly and the report’s conclusions are appropriate in light of the results.”

The fact that the authors were, as I mentioned in my response below, transparent about all the pieces of the study, the review process, and the funding sources should lead people to have a lot more confidence in this piece of research than in unnamed, un-reviewed, or non-transparent studies that people sometimes push back with.

The concern about non-sold homes is also addressed in the FAQ (emphasis added):

“Have you accounted for the possibility that homes close to turbines didn’t sell because no one would buy them?

“Yes. If a home was on the market but could not attract a buyer, it is assumed that that the seller would reduce the price. Therefore, if a house near a wind turbine was considered to be affected, it would be reflected in the data as a lower sales price. In the case that no buyers could be found at any price, one would expect to see these homes sell less frequently. The authors specifically tested to see if this had occurred and found that homes close to turbines sold at the same rate as homes farther away from turbines. In fact, the data included 1,503 sales that actually occurred between 1998 and 2012 within one mile of turbines after the turbines were constructed.”

Marie Jane

You say: “A new study looked at how well wind turbines and homes fit together in Massachusetts, and found no evidence that wind turbines affect property values.”

First, let me say that it saddens me to think that as a scientist you support the industrial wind turbine agenda and its destructive nature. You support the destruction of natural habitats and natural resources which are millions of years old in support of an archaic technology with a 15 – 20 year life expectancy. Not to mention the negative effect on human kind and, also, their property values.

Second, let me say, that if Mr. Hoen, et al, were looking for affects on property values, he would have found them. He was instead underwriting the goals of the industrial wind turbine agenda in the State of Massachusetts. A look at the financial support of his study will verify.

Might I suggest to you that you read the following from today’s Boston Globe (1/25/2014):

According to Mr. Hoen, his data was collected from 1998 to December 31, 2011. Hoosac went up in 2012, Falmouth March 2010, Scituate March 2012, Kingston (large scale) ground breaking September 2011, Fairhaven May 20I2, Gloucester up November 2012 and operating December 2012 (when checking, there are minor discrepancies between construction/operating and commission dates, but I feel these dates/years are close enough, given the information available, to accurately express and address my concerns about the credibility of this, taxpayer paid for, $70,000 “study”.)

Why does Mr. Hoen use property sales from 1998 to December 31, 2011 (this according to Mr. Hoen during his webinar), and why is sale year 2012 omitted (see *chart below from Hoen study). I do believe that 2012 would have been a very significant year in the study of the impact of the industrial wind turbine on residential sales in Massachusetts. And why does he use 122,000 homes/transactions? His method and conclusions defy logic. It speaks volumes about MA CEC, DOE, Berkeley and those with a personal agenda touting this as fact in support of the furtherance of the industrial wind turbine agenda.

The locations of every wind turbine in Massachusetts is known, the day they became operational is known, the day resident complaints started is known, and home sales dates are known and could be measured pre and post construction of the various projects with pinpoint accuracy given sales data available through Multiple Listing Service.

Every Appraiser lives by a Code of Professional Ethics and Standards of Professional Appraisal Practice, violations of which can result in remedial or disciplinary actions. Why was this study not given to an independent, licensed Appraiser from Massachusetts, knowledgeable in property values in the State of Massachusetts?

The study data was, in fact collected from 1998 to December 31, 2011. How, then, can this possibly show accurate or, for that matter, any information for installations done from 2011 through 2012? Page 2 note from Hoen study: “The analysis focuses on the 41 turbines in Massachusetts that are larger than 600 kilowatt and that were operating as of November 2012.”

(I apologize for the way this chart presents, you will find it in graph form on page 46 of the “study”, sales years 1998 through 2011.)

*Sales:

sale year

1998

-0.52

0.007

-73.48

0.000

1999

-0.41

0.007

-58.44

0.000

2000

-0.26

0.007

-37.59

0.000

2001

-0.13

0.007

-18.03

0.000

2002

0.02

0.007

2.33

0.020

2003

0.14

0.007

21.26

0.000

2004

0.24

0.007

37.05

0.000

2005

0.31

0.006

49.32

0.000

2006

0.28

0.006

43.94

0.000

2007

0.23

0.006

37.58

0.000

2008

0.12

0.006

18.43

0.000

2009

0.04

0.006

7.29

0.000

2010

0.04

0.006

6.15

0.000

2011

-0.02

0.006

-3.74

0.000

2012

Omitted

Note, most of Mr. Hoen’s references say “to 2012” (I would interpret this as “not including” 2012). Note in the chart, he ends abruptly at 2011 confirming his webinar statement and intentionally omits 2012. There are reports in his study authored by other researches identified by him as sources of information, the dates of which include the years 2012 and 2013, but no such current information about the impact industrial wind turbines have on property values.

Thanks for weighing in, Marie Jane. I do support wind power, as one of our best opportunities for reducing the many negative impacts of our current power plant fleet — including, certainly, climate change. Understanding and promoting an understanding of the costs and benefits, the risks and opportunities, of the whole range of generation options is key for good decision making by those proposing energy options and by those of us evaluating them.

This study clearly fits that framework. The authors were transparent about their assumptions, their data sources, their methodology, and their results, along with their funding sources and their reviewers. That approach gives us the ability to evaluate and respond accordingly.

As for the timing of the data, they needed a robust set of data from before installation and after to make the results valid. Newer installations would presumably not have had time to generate enough post-construction data to ensure robustness at the time the authors were collecting and analyzing.

I very much share your interest, though, in seeing periodic updates to this study that take even more turbines and transactions into account.